Me in Blue Ridge Parway, North Carolina, United States
Biography

Hi, I am Sadman Sadeed Omee.

I am a Ph.D. Candidate in the Department of Computer Science and Engineering at the University of South Carolina. I am advised by Dr. Jianjun Hu, and I work as a Graduate Research Assistant in the Machine Learning and Evolution Laboratory under his supervision. My field of research is solving materials informatics problems using Deep Learning techniques.

I am born and raised in Bangladesh. I have completed my B.S. in Computer Science and Engineering from Bangladesh University of Engineering and Technology in 2019. My aim is to become an effective and impactful Deep Learning Scientist.

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Education
 
 
 
 
 
UofSC logo

University of South Carolina

Ph.D.
Computer Science
August 2021 - Current
 
 
 
 
 
BUET logo

Bangladesh University of Engineering and Technology

B.S.
Computer Science and Engineering
February 2015 - April 2019
Experience
 
 
 
 
 
UofSC logo

Graduate Research Assistant

Machine Learning and Evoluation Laboratory
Department of Computer Science and Engineering
University of South Carolina
Columbia, South Carolina, United States
January 2022 - Current
  • Research topic: I use deep learning techniques to solve materials informatics problems (e.g., crystal structure prediction, materials property prediction)
  • Concept / skills usage: I use mostly Graph Neural Networks (GNNs) for my research. I have also used Convolutional Neural Networks, Transformers and Generative Models for my other researches. I am fluent in using PyTorch and PyTorch Geometric.
 
 
 
 
 
UofSC logo

Graduate Teaching Assistant

Course: General Applications Programming (CSCE 102)
Department of Computer Science and Engineering
University of South Carolina
Columbia, South Carolina, United States
August 2021 - December 2021, August 2023 - Current
  • Taught HTML, CSS, and JavaScript to a total of 72 students, and two lab group of total 50 students.
Research

My Research is on Deep Learning in Materials Informatics.

We use deep learning techniques to solve materials informatics problems (e.g., crystal structure prediction, materials property prediction) in our lab. My work on crystal structure prediction is similar to the protein structure prediction problem solved by AlphaFold2. I have also developed a state-of-the art global attention-based Graph Neural Network architecture.

I mostly use Graph Neural Networks (GNNs) for my research. I have also used Convolutional Neural Networks, Transformers and Generative Models for my other researches. I am fluent in using PyTorch and PyTorch Geometric.

Publications
Journal Papers
  • DeeperGATGNN logo

    Scalable Deeper Graph Neural Networks for High-Performance Materials Property Prediction

    Sadman Sadeed Omee, Steph-Yves Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu
    Patterns
    2022
  • Materials Property Prediction with Uncertainity Estimation: A Benchmark Study

    Daniel Varivoda, Rongzhi Dong, Sadman Sadeed Omee, Jianjun Hu
    Applied Physics Reviews
    2023
  • MaterialsAtlas.org: A Materials Informatics Web App Platform for Materials Discovery and Survey of State-of-the-Art

    Jianjun Hu, Stanislav Stefanov, Yuqi Song, Sadman Sadeed Omee, Steph-Yves Louis, Edirisuriya M. D. Siriwardane, Yong Zhao
    npj Computational Materials
    2022
  • Accurate Prediction of Voltage of Battery Electrode Materials Using Attention Based Graph Neural Networks

    Steph-Yves Louis, Edirisuriya M. D. Siriwardane, Rajendra P. Joshi, Sadman Sadeed Omee, Neeraj Kumar, Jianjun Hu
    ACS Applied Materials & Interfaces
    2022
  • DeepXRD: A Deep Learning Model for Predicting XRD Spectrum from Materials Composition

    Rongzhi Dong, Yong Zhao, Yuqi Song, Nihang Fu, Sadman Sadeed Omee, Sourin Dey, Qinyang Li, Lai Wei, Jianjun Hu
    ACS Applied Materials & Interfaces
    2022
  • Global Mapping of Structures and Properties of Crystal Materials

    Qinyang Li, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee, Lai Wei, Jianjun Hu
    Journal of Chemical Information and Modeling
    2023
  • Towards Quantitative Evaluation of Crystal Structure Prediction Performance

    Lai Wei, Qin Li, Sadman Sadeed Omee, Jianjun Hu
    Computational Materials Science
    2024
  • TCSP: A Template-Based Crystal Structure Prediction Algorithm for Materials Discovery

    Lai Wei, Nihang Fu, Edirisuriya M. D. Siriwardane, Wenhui Yang, Sadman Sadeed Omee, Rongzhi Dong, Rui Xin, Jianjun Hu
    Inorganic Chemistry
    2022
  • Material Transformers: Deep Learning Language Models for Generative Materials Design

    Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M Dilanga Siriwardane, Jianjun Hu
    Machine Learning: Science and Technology
    2023
Book Chapters
  • Evolutionary Machine Learning in Science and Engineering

    Jianjun Hu, Yuqi Song, Sadman Sadeed Omee, Lai Wei, Rongzhi Dong, Siddharth Gianey
    Handbook of Evolutionary Machine Learning
    2023
Submitted Manuscripts
  • Structure-Based Out-of-Distribution (OOD) Materials Property Prediction: A Benchmark Study

    Sadman Sadeed Omee, Nihang Fu, Rongzhi Dong, Ming Hu, Jianjun Hu
    2024
  • Crystal Structure Prediction Using Neural Network Potential and Age-Fitness Pareto Genetic Algorithm

    Sadman Sadeed Omee, Lai Wei, Ming Hu, Jianjun Hu
    2023
  • MD-HIT: Machine Learning for Materials Property Prediction with Dataset Redundancy Control

    Qin Li, Nihang Fu, Sadman Sadeed Omee, Jianjun Hu
    2023
CV / Resume

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Blogs

I will try to write blogs on Machine Learning and Deep Learning concepts. I will also try to cover some important research papers in this field and some of my own papers.

Coming soon ... !

Contact